In recent years functional MRI studies of human reward learning have signicantly advanced our understanding of how the brain represents rewards and learns reward associations. The studies presented in this thesis build on this work to further char- acterize the functional contributions of regions such as the orbitofrontal cortex and ventral striatum, with a focus on understanding how neural activity relates to behav- ior, specically in terms of valuation and decision-making.
Attractive faces have been shown to be a form of visual reward, suggesting that they should aect behavior and neural activity in a manner similar to other types of reinforcers. In Chapter 1 we tested this hypothesis and demonstrated that attractive faces can act as reinforcers in a classical conditioning paradigm. The aective pleas- antness of a set of neutral visual cues increased as a result of repeated pairings with attractive, compared to unattractive, female faces. We found that reward prediction errors in the ventral striatum were engaged during learning, as has been found for other types of reinforcers such as food, pain, and money.
The change in valuation for cues paired with attractive female faces was especially pronounced in male subjects, while female subjects did not show a similar eect in response to male faces. Interestingly, in male subjects prediction error responses were strongest for female faces, and prediction error responses in female subjects were strongest for male faces. This suggests that learning takes place similarly in the brains of male and female subjects, but is expressed dierently at the behavioral level. An avenue for future study would be to employ dierent behavioral probes to
investigate if and how female subjects express this learning.
More generally the results of this study are relevant for marketing studies, which have shown that the presence of an attractive female model in an advertisement can inuence customer perception of a product [101, 102]. Our ndings suggest that classical conditioning mechanisms may contribute to this eect.
Pavlovian cues elicit passive responses but can also exert control over instrumen- tal responding. In Chapter 2 we presented the rst investigation into the neural mechanisms by which Pavlovian cues exert control over human decision-making. We showed that a Pavlovian cue predictive of a specic liquid reward can bias action choice towards responses associated with the same liquid reward. We found that a region of ventrolateral putamen was relatively suppressed when subjects made choices incompatible with the Pavlovian cue. While lesion studies in animals have shown that regions of ventral striatum are necessary for the expression of Pavlovian-instrumental transfer eects [83], this study is the rst to show the dynamics of neural activity involved in outcome-specic transfer.
Current theories propose that transfer mechanisms are mediated by stimulus- outcome and outcome-response associations [79]. Our results t nicely with this theory: we interpret our nding of a relative suppression when an incompatible cue is chosen as related to the suppression of an outcome-response association stimulated by the Pavlovian cue.
We note that the regions we found to be involved in outcome-specic transfer are distinct from those found in a recent fMRI study on general transfer eects, in which a Pavlovian cue enhances response vigor rather than inuencing decision-making per se [86]; this mirrors the dissociation in neural circuitry found in animal studies of general and specic transfer eects [83, 84, 85]. However, it will be important in future studies to demonstrate both general and specic transfer eects in the same paradigm.
Several interesting features of Pavlovian-instrumental paradigms have been iden- tied in the animal literature, of particular interest is the eect of reinforcer devalua- tion. It has been shown that in certain situations devaluing the reinforcer associated
with the Pavlovian cue does not suppress the expression of transfer eects in animals [148, 79]. This nding has clear parallels with addictive behaviors, in which environ- mental cues trigger drug-seeking, even when the outcome has known aversive eects.
Few studies have directly probed the links between transfer eects and addictive be- haviors [150], but this line of research could prove important in understanding the neurophysiological underpinnings of addiction. One potential avenue for treatment could involve training subjects to suppress regional activity in order to successfully avoid making choices associated with environmental cues [100, 160].
A further extension of the work presented in chapters 1 and 2, related to the impact of attractive faces used in advertising, would be to test whether cues associated with attractive faces can exert control over instrumental behaviors, as has been shown with other types of reinforcers [150, 86].
In Chapters 3 and 4 we investigate how provision of reward can inuence neural plasticity: we trained human subjects to activate specic brain regions in order to earn reward. We demonstrated that a shaping procedure in which subjects were given monetary rewards for making improvements on their past performance was successful in training an increase in dierential activity across sessions. This technique presents an alternative to standard bio/neurofeedback approaches and may prove useful in many clinical and research applications.
In the study described in Chapter 3 we successfully trained subjects to dieren- tially activate regions of motor cortex related to hand and foot movements, in absence of overt movements. We investigated behavioral eects of this learning, and showed that reaction times in a cued response task were dierentially aected by presentation of the learned cues.
A primary motivation for developing this technique was to condition neural activ- ity in emotional brain regions, in order to study the causal eects of elevated activity on behavior. In the study described in Chapter 4 we trained subjects to activate me- dial orbitofrontal cortex (mOFC) activity and probed the impact of this training on an aective judgment task. We demonstrated that subjects can improve at elevating mOFC activity on cue, and that elevated activity was associated with a positive bias
in aective evaluations. This study represents a signicant advance in our under- standing of how mOFC activity aects our perception of value, as previous imaging studies have been unable to establish this causal link.
Taken together, these studies advance our understanding of the functional con- tributions of ventral striatum and orbitofrontal cortex in inuencing decision-making and valuation, and suggest that applying associative learning techniques to real-time fMRI training can be a powerful method for characterizing the causal inuence of regional neural activity.
Bibliography
[1] I. Pavlov, Conditioned refelxes: An investigation of the physiological activity of the cerebral cortex, 1927.
[2] E. Thorndike, Animal Intelligence. New York: Macmillan, 1911.
[3] B. F. Skinner, The behavior of organisms. New York: Appleton-Century-Crofts, 1938.
[4] B. F. Skinner, Science and human behavior. New York: MacMillan, 1953.
[5] F. D. Sheeld, J. J. Wul, and R. Backer, Reward value of copulation with- out sex drive reduction, Journal of comparative and physiological psychology, vol. 44, pp. 38, 1951.
[6] D. A. Lieberman, Learning: Behavior and Cognition. Stamford CT: Wadsworth, 3 ed., 2000.
[7] F. Etscorn and R. Stephens, Establishment of conditioned taste aversions with a 24-hour cs-us interval, Physiological Psychology, vol. 1, no. 3, pp. 251253, 1973.
[8] R. A. Rescorla, Predictability and number of pairings in pavlovian fear condi- tioning, Psychonomic Science, vol. 4, no. 11, pp. 383384, 1966.
[9] L. Kamin, Predictability, surprise, attention, and conditioning, in Punishment and aversive behavior (C. R. Campbell, BA, ed.), New York: Appleton-Century- Crofts, 1969.
[10] R. A. Rescorla and A. R. Wagner, A theory of pavlovian conditioning: Varia- tions in eectiveness of reinforcement and nonreinforcement, in Classical Con- ditioning II: Current research and theory (A. H. Black and W. F. Prokasy, eds.), New York: Appleton Century-Crofts, 1972.
[11] R. S. Sutton, Learning to predict by the methods of temporal dierences, Machine Learning, vol. 3, pp. 944, 1988.
[12] E. R. Siquelan and C. A. Delucia, Visual reinforcement of nonnutritive sucking in human infants, Science, vol. 165, no. 3898, p. 1144, 1969. Times Cited: 87.
[13] R. A. Butler, Incentive conditions which inuence visual exploration, Journal of Experimental Psychology, vol. 48, no. 1, pp. 1923, 1954.
[14] R. J. Lamb, A. R. Morral, G. Galbicka, K. C. Kirby, and M. Y. Iguchi, Shaping reduced smoking in smokers without cessation plans, Experimental and Clinical Psychopharmacology, vol. 13, no. 2, pp. 8392, 2005.
[15] E. S. Athens, T. R. Vollmer, and C. Pipkin, Shaping academic task engagement with percentile schedules, Journal of Applied Behavior Analysis, vol. 40, no. 3, pp. 475488, 2007.
[16] G. Galbicka, Shaping in the 21st century: moving percentile schedules into applied settings, Journal of Applied Behavior Analysis, vol. 27, no. 4, pp. 739 760, 1994.
[17] D. Hebb, The organization of behavior. New York: Wiley, 1949.
[18] G. Q. Bi and M. M. Poo, Synaptic modication by correlated activity: Hebb's postulate revisited, Annual Review of Neuroscience, vol. 24, pp. 139166, 2001.
[19] R. Dias, T. W. Robbins, and A. C. Roberts, Dissociation in prefrontal cortex of aective and attentional shifts, Nature, vol. 380, no. 6569, pp. 6972, 1996.
[20] J. Hornak, J. O'Doherty, J. Bramham, E. T. Rolls, R. G. Morris, P. R. Bullock, and C. E. Polkey, Reward-related reversal learning after surgical excisions in
orbito-frontal or dorsolateral prefrontal cortex in humans, Journal of Cognitive Neuroscience, vol. 16, no. 3, pp. 463478, 2004.
[21] J. L. Price, Olfactory system, in The Human Nervous System (G. Paxinos, ed.), San Diego: Academic, 1990.
[22] J. L. Price, Denition of the orbital cortex in relation to specic connections with limbic and visceral structures and other cortical regions, 2007.
[23] L. L. Baylis, E. T. Rolls, and G. C. Baylis, Aerent connections of the cau- dolateral orbitofrontal cortex taste area of the primate, Neuroscience, vol. 64, no. 3, pp. 801812, 1995.
[24] E. T. Rolls and L. L. Baylis, Gustatory, olfactory, and visual convergence within the primate orbitofrontal cortex, Journal of Neuroscience, vol. 14, no. 9, pp. 54375452, 1994.
[25] B. J. Rolls, E. T. Rolls, E. A. Rowe, and K. Sweeney, Sensory specic satiety in man, Physiology and Behavior, vol. 27, no. 1, pp. 137142, 1981.
[26] H. D. Critchley and E. T. Rolls, Hunger and satiety modify the responses of olfactory and visual neurons in the primate orbitofrontal cortex, Journal of Neurophysiology, vol. 75, no. 4, pp. 16731686, 1996.
[27] E. T. Rolls, Z. J. Sienkiewicz, and S. Yaxley, Hunger modulates the responses to gustatory stimuli of single neurons in the caudolateral orbitofrontal cortex of the macaque monkey, European Journal of Neuroscience, vol. 1, no. 1, pp. 53 60, 1989.
[28] J. O'Doherty, E. T. Rolls, S. Francis, R. Bowtell, and F. McGlone, Represen- tation of pleasant and aversive taste in the human brain, Journal of Neuro- physiology, vol. 85, no. 3, pp. 13151321, 2001.
[29] E. T. Rolls, M. L. Kringelbach, and I. E. T. de Araujo, Dierent representations of pleasant and unpleasant odours in the human brain, European Journal of Neuroscience, vol. 18, no. 3, pp. 695703, 2003. Times Cited: 83.
[30] I. Aharon, N. Etco, D. Ariely, C. F. Chabris, E. O'Connor, and H. C. Breiter, Beautiful faces have variable reward value: fmri and behavioral evidence, Neuron, vol. 32, pp. 537551, 2001.
[31] J. O'Doherty, J. Winston, H. Critchley, D. Perrett, D. M. Burt, and R. J.
Dolan, Beauty in a smile: the role of medial orbitofrontal cortex in facial attractiveness, Neuropsychologia, vol. 41, pp. 147155, 2003.
[32] A. J. Blood and R. J. Zatorre, Intensely pleasurable responses to music cor- relate with activity in brain regions implicated in reward and emotion, Pro- ceedings of the National Academy of Sciences of the United States of America, vol. 98, no. 20, pp. 1181811823, 2001.
[33] J. O'Doherty, E. T. Rolls, S. Francis, R. Bowtell, F. McGlone, G. Kobal, B. Ren- ner, and G. Ahne, Sensory-specic satiety-related olfactory activation of the human orbitofrontal cortex,
[34] R. Elliott, C. D. Frith, and R. J. Dolan, Dierential neural response to posi- tive and negative feedback in planning and guessing tasks, Neuropsychologia, vol. 35, no. 10, pp. 13951404, 1997.
[35] R. Elliott, J. L. Newman, O. A. Longe, and J. F. W. Deakin, Dierential response patterns in the striatum and orbitofrontal cortex to nancial reward in humans: A parametric functional magnetic resonance imaging study, Journal of Neuroscience, vol. 23, no. 1, pp. 303307, 2003.
[36] H. C. Breiter, I. Aharon, D. Kahneman, A. Dale, and P. Shizgal, Functional imaging of neural responses to expectancy and experience of monetary gains and losses, Neuron, vol. 30, no. 2, pp. 619639, 2001.
[37] J. P. O'Doherty, R. Deichmann, H. D. Critchley, and R. J. Dolan, Neural responses during anticipation of a primary taste reward, Neuron, vol. 33, no. 5, pp. 815826, 2002.
[38] J. A. Gottfried, J. O'Doherty, and R. J. Dolan, Encoding predictive reward value in human amygdala and orbitofrontal cortex, Science, vol. 301, no. 5636, pp. 11041107, 2003.
[39] D. M. Small, R. J. Zatorre, A. Dagher, A. C. Evans, and M. Jones-Gotman, Changes in brain activity related to eating chocolate - from pleasure to aver- sion, Brain, vol. 124, pp. 17201733, 2001. Part 9.
[40] H. Plassmann, J. O'Doherty, and A. Rangel, Orbitofrontal cortex encodes will- ingness to pay in everyday economic transactions, Journal of Neuroscience, vol. 27, no. 37, pp. 99849988, 2007. Times Cited: 1.
[41] H. Plassmann, J. O'Doherty, B. Shiv, and A. Rangel, Marketing actions can modulate neural representations of experienced pleasantness, Proceedings of the National Academy of Sciences of the United States of America, vol. 105, pp. 10501054, 2008. Times Cited: 1.
[42] J. E. LeDoux, Emotion circuits in the brain, Annual Review of Neuroscience, vol. 23, pp. 155184, 2000.
[43] S. Maren and M. S. Fanselow, The amygdala and fear conditioning: Has the nut been cracked?, Neuron, vol. 16, no. 2, pp. 237240, 1996.
[44] L. M. Romanski and J. E. Ledoux, Equipotentiality of thalamoamygdala and thalamocorticoamygdala circuits in auditory fear conditioning, Journal of Neu- roscience, vol. 12, no. 11, pp. 45014509, 1992.
[45] S. Maren and M. S. Fanselow, Synaptic plasticity in the basolateral amyg- dala induced by hippocampal-formation stimulation in-vivo, Journal of Neu- roscience, vol. 15, no. 11, pp. 75487564, 1995.
[46] J. Hitchcock and M. Davis, Lesions of the amygdala, but not of the cerebellum or red nucleus, block conditioned fear as measured with the potentiated startle paradigm, Behavioral Neuroscience, vol. 100, no. 1, p. 11, 1986.
[47] L. D. Vandekar, R. A. Piechowski, P. A. Rittenhouse, and T. S.
Gray, Amygdaloid-lesions - dierential eect on conditioned stress and immobilization-induced increases in corticosterone and renin secretion, Neu- roendocrinology, vol. 54, no. 2, pp. 8995, 1991.
[48] A. Bechara, D. Tranel, H. Damasio, R. Adolphs, C. Rockland, and A. R. Dama- sio, Double dissociation of conditioning and declarative knowledge relative to the amygdala and hippocampus in humans, Science, vol. 269, no. 5227, pp. 11151118, 1995.
[49] J. J. Paton, M. A. Belova, S. E. Morrison, and C. D. Salzman, The primate amygdala represents the positive and negative value of visual stimuli during learning, Nature, vol. 439, no. 7078, pp. 865870, 2006.
[50] H. C. Breiter, N. L. Etco, P. J. Whalen, W. A. Kennedy, S. L. Rauch, R. L.
Buckner, M. M. Strauss, S. E. Hyman, and B. R. Rosen, Response and habit- uation of the human amygdala during visual processing of facial expression, Neuron, vol. 17, no. 5, pp. 875887, 1996.
[51] I. S. Johnsrude, A. M. Owen, N. M. White, W. V. Zhao, and V. Bohbot, Impaired preference conditioning after anterior temporal lobe resection in hu- mans, Journal of Neuroscience, vol. 20, no. 7, pp. 26492656, 2000.
[52] C. Buchel, J. Morris, R. J. Dolan, and K. J. Friston, Brain systems mediating aversive conditioning: an event-related fmri study, Neuron, vol. 20, no. 5, pp. 947957, 1998.
[53] W. Li, J. D. Howard, T. B. Parrish, and J. A. Gottfried, Aversive learning enhances perceptual and cortical discrimination of indiscriminable odor cues, Science, vol. 319, no. 5871, pp. 18421845, 2008.
[54] J. Olds and P. Milner, Positive reinforcement produced by electrical stimulation of septal area and other regions of rat brain, Journal of Comparative and Physiological Psychology, vol. 47, no. 6, pp. 419427, 1954.
[55] B. G. Hoebel, A. P. Monaco, L. Hernandez, E. F. Aulisi, B. G. Stanley, and L. Lenard, Self-injection of amphetamine directly into the brain, Psychophar- macology, vol. 81, no. 2, pp. 158163, 1983.
[56] W. A. Carlezon, D. P. Devine, and R. A. Wise, Habit-forming actions of nomifensine in nucleus-accumbens, Psychopharmacology, vol. 122, no. 2, pp. 194197, 1995.
[57] R. A. Wise, Brain reward circuitry: Insights from unsensed incentives, Neuron, vol. 36, no. 2, pp. 229240, 2002.
[58] W. Schultz, Getting formal with dopamine and reward, Neuron, vol. 36, no. 2, pp. 241263, 2002.
[59] R. Romo and W. Schultz, Dopamine neurons of the monkey midbrain - con- tingencies of responses to active touch during self-initiated arm movements, Journal of Neurophysiology, vol. 63, no. 3, pp. 592606, 1990.
[60] W. Schultz and R. Romo, Responses of nigrostriatal dopamine neurons to high-intensity somatosensory stimulation in the anesthetized monkey, Journal of Neurophysiology, vol. 57, no. 1, pp. 201217, 1987.
[61] W. Schultz and R. Romo, Dopamine neurons of the monkey midbrain - contin- gencies of responses to stimuli eliciting immediate behavioral reactions, Journal of Neurophysiology, vol. 63, no. 3, pp. 607624, 1990.
[62] J. Mirenowicz and W. Schultz, Preferential activation of midbrain dopamine neurons by appetitive rather than aversive stimuli, Nature, vol. 379, no. 6564, pp. 449451, 1996.
[63] J. Mirenowicz and W. Schultz, Importance of unpredictability for reward re- sponses in primate dopamine neurons, Journal of Neurophysiology, vol. 72, no. 2, pp. 10241027, 1994.
[64] J. R. Hollerman and W. Schultz, Dopamine neurons report an error in the temporal prediction of reward during learning, Nature Neuroscience, vol. 1, pp. 304309, 1998.
[65] I. Martin and A. B. Levey, Blocking observed in human eyelid condition- ing, Quarterly Journal of Experimental Psychology Section B-Comparative and Physiological Psychology, vol. 43, no. 3, pp. 233256, 1991.
[66] P. Waelti, A. Dickinson, and W. Schultz, Dopamine responses comply with basic assumptions of formal learning theory, Nature, vol. 412, no. 6842, pp. 43 48, 2001.
[67] R. S. Burns, C. C. Chiueh, S. P. Markey, M. H. Ebert, D. M. Jacobowitz, and I. J. Kopin, A primate model of parkinsonism - selective destruction of dopaminergic-neurons in the pars compacta of the substantia nigra by n-methyl- 4-phenyl-1,2,3,6-tetrahydropyridine, Proceedings of the National Academy of Sciences of the United States of America-Biological Sciences, vol. 80, no. 14, pp. 45464550, 1983.
[68] A. M. J. Young, M. H. Joseph, and J. A. Gray, Increased dopamine release invivo in nucleus-accumbens and caudate-nucleus of the rat during drinking - a microdialysis study, Neuroscience, vol. 48, no. 4, pp. 871876, 1992.
[69] G. S. Berns, S. M. McClure, G. Pagnoni, and P. R. Montague, Predictability modulates human brain response to reward, Journal of Neuroscience, vol. 21, no. 8, pp. 27932798, 2001.
[70] G. Pagnoni, C. F. Zink, P. R. Montague, and G. S. Berns, Activity in human ventral striatum locked to errors of reward prediction, Nature Neuroscience, vol. 5, no. 2, pp. 9798, 2002.
[71] J. P. O'Doherty, P. Dayan, K. Friston, H. Critchley, and R. J. Dolan, Temporal dierence models and reward-related learning in the human brain, Neuron, vol. 38, pp. 329337, 2003.
[72] B. Seymour, N. Daw, P. Dayan, T. Singer, and R. Dolan, Dierential encoding of losses and gains in the human striatum, Journal of Neuroscience, vol. 27, no. 18, pp. 48264831, 2007.
[73] P. N. Tobler, J. P. O'Doherty, R. J. Dolan, and W. Schultz, Human neural learning depends on reward prediction errors in the blocking paradigm, Journal of Neurophysiology, vol. 95, no. 1, pp. 301310, 2006.
[74] M. R. Delgado, L. E. Nystrom, C. Fissell, D. C. Noll, and J. A. Fiez, Tracking the hemodynamic responses to reward and punishment in the striatum, Journal of Neurophysiology, vol. 84, no. 6, pp. 30723077, 2000.
[75] C. F. Zink, Y. X. Tong, Q. Chen, D. S. Bassett, J. L. Stein, and A. Meyer- Lindenberg, Know your place: Neural processing of social hierarchy in hu- mans, Neuron, vol. 85, no. 2, pp. 273283, 2008.
[76] B. Wansink, M. M. Cheney, and N. Chan, Exploring comfort food preferences across age and gender, Physiology and Behavior, vol. 79, no. 4-5, pp. 739747, 2003.
[77] W. K. Estes, Discriminative conditioning i a discriminative property of con- ditioned anticipation, Journal of Experimental Psychology, vol. 32, no. 2, pp. 150155, 1943.
[78] W. K. Estes, Discriminative conditioning 2 eects of a pavlovian conditioned stimulus upon a subsequently established operant response, Journal of Exper- imental Psychology, vol. 38, no. 2, pp. 173177, 1948.
[79] R. A. Rescorla, Transfer of instrumental control mediated by a devalued out- come, Animal Learning and Behavior, vol. 22, no. 1, pp. 2733, 1994.
[80] P. Blundell, G. Hall, and S. Killcross, Lesions of the basolateral amygdala disrupt selective aspects of reinforcer representation in rats, Journal of Neu- roscience, vol. 21, no. 22, pp. 90189026, 2001.
[81] G. Bower and R. Kaufman, Transfer across drives of discriminative eect of a pavlovian conditioned stimulus, Journal of the Experimental Analysis of Be- havior, vol. 6, no. 3, p. 445, 1963.
[82] B. Balleine, Asymmetrical interactions between thirst and hunger in pavlovian- instrumental transfer, Quarterly Journal of Experimental Psychology Section B-Comparative and Physiological Psychology, vol. 47, no. 2, pp. 211231, 1994.
[83] L. H. Corbit, J. L. Muir, and B. W. Balleine, The role of the nucleus accumbens in instrumental conditioning: Evidence of a functional dissociation between accumbens core and shell, Journal of Neuroscience, vol. 21, no. 9, pp. 3251 3260, 2001.
[84] L. H. Corbit and B. W. Balleine, Double dissociation of basolateral and cen- tral amygdala lesions on the general and outcome-specic forms of pavlovian- instrumental transfer, Journal of Neuroscience, vol. 25, no. 4, pp. 962970, 2005.
[85] L. H. Corbit and P. H. Janak, Inactivation of the lateral but not medial dorsal striatum eliminates the excitatory impact of pavlovian stimuli on instrumental responding, Journal of Neuroscience, vol. 27, no. 51, pp. 1397713981, 2007.
[86] D. Talmi, B. Seymour, P. Dayan, and R. J. Dolan, Human pavlovian- instrumental transfer, Journal of Neuroscience, vol. 28, no. 2, pp. 360368, 2008.
[87] E. E. Fetz, Operant conditioning of cortical unit activity, Science, vol. 163, no. 3870, p. 955, 1969.
[88] J. V. Basmajian, Control and training of individual motor units, Science, vol. 141, no. 357, p. 440, 1963.
[89] J. Olds and M. Olds, Inference and learning in paleocortical systems, in Brain mechanisms and Learning (A. Fessard, R. Gerard, and J. Konorski, eds.), Ox- ford: Blackwell Scientic Publications, 1961.
[90] E. B. Fetz and FinocchiDv, Operant conditioning of specic patterns of neural and muscular activity, Science, vol. 174, no. 4007, p. 431, 1971. Times Cited:
66.
[91] A. Pascual-Leone, D. Bartres-Faz, and J. P. Keenan, Transcranial magnetic stimulation: studying the brain-behaviour relationship by induction of 'virtual lesions',
[92] N. Birbaumer, A. Kubler, N. Ghanayim, T. Hinterberger, J. Perelmouter, J. Kaiser, I. Iversen, B. Kotchoubey, N. Neumann, and H. Flor, The thought translation device (ttd) for completely paralyzed patients, Ieee Transactions on Rehabilitation Engineering, vol. 8, no. 2, pp. 190193, 2000.
[93] J. R. Wolpaw, D. J. McFarland, G. W. Neat, and C. A. Forneris, An eeg- based brain-computer interface for cursor control, Electroencephalography and Clinical Neurophysiology, vol. 78, no. 3, pp. 252259, 1991.
[94] S. Musallam, B. D. C. BD, B. Greger, H. Scherberger, and R. A. Andersen, Cognitive control signals for neural prosthetics, Science, vol. 305, no. 5681, pp. 258262, 2004.
[95] M. Velliste, S. Perel, M. C. Spalding, A. S. Whitford, and A. B. Schwartz, Cortical control of a prosthetic arm for self-feeding, Nature, 2008. 0028-0836 101038/nature06996 101038/nature06996.
[96] R. C. deCharms, K. Christo, G. H. Glover, J. M. Pauly, S. Whiteld, and J. D. E. Gabrieli, Learned regulation of spatially localized brain activation using real-time fmri, Neuroimage, vol. 21, pp. 436443, 2004.
[97] S. Posse, D. Fitzgerald, K. X. Gao, U. Habel, D. Rosenberg, G. J. Moore, and F. Schneider, Real-time fmri of temporolimbic regions detects amygdala